/// <summary>
/// Runs the input through the CoreML model
/// </summary>
/// <param name="input">The input data to the model.</param>
/// <returns>The output of the CoreML model.</returns>
private MLMultiArray Predict(MLMultiArray input)
{
var inputFeatureProvider = new ImageInputFeatureProvider(inputFeatureName)
{
ImagePixelData = input
};
MLMultiArray result = this.mlModel.GetPrediction(inputFeatureProvider, out NSError modelErr)
.GetFeatureValue(outputFeatureName)
.MultiArrayValue;
return(result);
}
/// <summary>
/// Extract the direct output from MLCore without post-processing
/// </summary>
/// <returns>A tuple contain the two matrices output by the model. First matrix: the box prediction encoding; second matrix: the class logit for each box.</returns>
/// <param name="input"> The formatted matrix representation of image after proper transpose and normalization</param>
private (MLMultiArray, MLMultiArray) RawPredict(MLMultiArray input)
{
var inputFeatureProvider = new ImageInputFeatureProvider(_inputFeatureName)
{
ImagePixelData = input
};
var resultBundle = _mlModel.GetPrediction(inputFeatureProvider, out _);
var output1 = resultBundle.GetFeatureValue(Constants.ModelOutputBoxFeatureName).MultiArrayValue;
var output2 = resultBundle.GetFeatureValue(Constants.ModelOutputClassFeatureName).MultiArrayValue;
inputFeatureProvider.Dispose();
return(output1, output2);
}
